“I’m working on a Multi-Objective Bayesian Optimization (MOBO) problem involving a system with roughly 60 input parameters and around 30 performance evaluation metrics that we would ideally like to ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: Multi-party multi-objective optimization, which aims to find a solution set that satisfies multiple decision makers (DMs) as much as possible, has attracted the attention of researchers ...

Abstract: Multi-objective evolutionary algorithms (MOEAs) have achieved notable success in recommendation systems (RSs) by meeting diverse user needs. However, existing MOEAs lack effective methods to ...

In International Conference on Evolutionary Multi-objective Optimization. DOI: 10.1007/978-981-96-3538-2_9 [arXiv] The paper introduces an acquisition function for finding the Pareto front of a ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

This paper addresses the shortcomings of the Sparrow and Eagle Optimization Algorithm (SBOA) in terms of convergence accuracy, convergence speed, and susceptibility to local optima. To this end, an ...